In 2008, Max Yankelevich was in India, visiting the cubicle farms where big banks and insurance companies outsource business processes — the invoices, memos, and other papers pushed to keep organizations humming.
Globally, it's a $27 billion industry.
The employees were smart, says Yankelevich, who was running a cloud computing startup at the time. There was good money in doing this sort of back office work — but it was mind numbing. You'd fall asleep at your desk in the middle of a loan document.
Companies were trying to figure out the back office work with "the brute force of human power," says Yankelevich, who studied artificial intelligence while getting his MIT computer science degree in the 1990s.
"I started thinking ... there’s gotta be a way where artificial intelligence can be used generically enough to learn some of these things that these people are doing," he says.
That wish became WorkFusion, the startup Yankelevich cofounded in 2010.
His thinking: If the world's most powerful corporations outsourced their repetitive knowledge work — much like what Yankelevich saw in India — to his team's algorithms rather than overseas, WorkFusion could land a chunk of what McKinsey has described as a $5 to $7 trillion opportunity for the automation of knowledge work.
WorkFusion does this by combining crowdsourcing with artificial intelligence. The company has made deals with freelance labor markets around the world (think gig economy platforms like Amazon Turk or Craigslist) to take care of the business processes that corporations want to outsource.
The 35 million people that have worked on the WorkFusion platform generate tons of data around how to do business-related tasks. WorkFusion's algorithm study those tasks using machine learning, the artificial intelligence technique that Google heavyweight Eric Schmidt says will be behind every significant tech IPO over the next five years.
With machine learning, algorithms learn from experience, rather than having to be programmed to execute prescribed actions. It's how self-driving cars recognize pedestrians and how algorithms can learn how to play video games.
WorkFusion's algorithms look over the shoulder of workers, gathering data on what they do, and selecting the best work to add to the data set. Then, over time, a given task become less human-executed and more computer-executed. If the algorithm runs into a problem it doesn't understand, it brings in the human worker, like how a "driver" in a driverless car can use the steering wheel and pedals if anything goes awry.
An ecommerce company like Amazon might come to WorkFusion for product catalog cleansing, Yankelevich says. With hundreds of millions of products listed, some of those items might have faulty data that prevents the appropriate result from coming up in search (like a misspelling of i-Pad instead of iPad). That job would be split up between WorkFusion's human freelance labor force and algorithms.
"Over time, robots take over more and more and automate more and more of that work," he says, with the hope that the people mired in these tasks would be able to tackle more creative work.
WorkFusion isn't the only company in the automating work. IBM has its Watson "cognitive computing" initiative, IPSoft is creating a "virtual employee" that can interact with customers in 20 languages, and Nuance is on its way to automating call centers.
In the same way that factory machines took over repetitive physical labor during the Industrial Revolution, algorithmic machines are on their way to taking over repetitive cognitive labor.
For WorkFusion, it could be the start of something big.
"Because of all the inputs being submitted from different customers, the underlying AI brain is starting to be able to get smarter and smarter and developing new neurons and being able to connect the dots much faster," Yankelevich says. "That happens just because if you service a lot of customers in a lot of different areas, AI can find parallels and eventually be able to be proactive about things."
As WorkFusion's AI gets more and more experience across a range of tasks, it will get better at figuring out how to do various jobs. While Yankelevich is careful to say that it won't be like Skynet from Terminator gaining consciousness and taking over the world, there's a real possibility that WorkFusion's AI will gain "a level of self-awareness"— and take over lots of business.
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